🎊 AI Spotlight: Savita Kini 🎊

We’re excited to present Savita Kini, Head of Products - AI/ML, Speech & Computer Vision at Cisco  as this week’s AI Spotlight. 

Let’s dive into our interview with Savita and see how she is using AI.

1. Share your AI origin story

My first exposure to neural networks was in undergrad, when I worked on a paper about a 3 layer neural network for load forecasting. It was very early in the 90s. I was fascinated about how these neural networks were mimicking the human brain. However, career opportunity took me to the networking industry. As I started working on vertical solutions in healthcare, education, smart cities / IOT etc - I realized the need for more intelligent edge for IOT aka need for AI type technology to help is better analyze the information available at the edge. In healthcare - personalized medicine is much needed, including in better diagnosis and research. In education - how to enable every child to succeed and how to democratize learning by making content available in all languages with automated translations etc. As data science matured, I realized around 2017/18 -- that we are entering a new phase of technological maturing for AI/ML. Some of the early signs were in language, speech and computer vision with the proliferation of autonomous vehicle startups and technology vendors. I wanted to embrace this new shift which was aligned with my dream as a young engineering student. I am lucky to have joined the BabbleLabs team and embarked on this journey building industry first speech enhancement models. Subsequent to the acquisition by Cisco, I expanded my responsibilities to include computer vision, which was fascinating learning. and since the GenAI inflection, am learning about GenAI models, Agentic systems and more. I am especially concerned about biases across all these different fields of AI/ML. 

2. What three AI tools have been most game changing for you? 

ChatGPT, Claude, Google Gemini, Siri, Perplexity

3. If you were just starting your AI journey today where would you start? 

Podcasts, Youtube, Coursera or similar online courses, Meetups for in-person learning and networking

4. Share the spotlight: Name 3+ women leading in AI we should all follow. 

Dr. anima Anandkumar, Dr. Anjana Susurula, Raquel Urtasun

5. As a woman in AI, what do you want our allies to know? 

AI systems need diverse teams from product, engineering, UX including data. We need to embrace the diversity of humanity as we build systems for wide use across the world. 

Special Series: Women's History Month

1. Can you share an example of how AI can be used to address gender-specific challenges or inequalities?

   Humans are fundamentally biased - elementary school, high school, college admissions, recruitment, promotions -- there is tons of data around communications in classrooms to boardroom how girls and women are "genderized" into learning paradigms, roles and responsibilities. I strongly believe that AI can actually be used to address / catch human biases especially unconscious bias in such situations.
   

2. How do you envision AI shaping the future of women's rights and opportunities?

   
   

   I am not sure here AI will shape future of women's rights -- we need women to standup for themselves, willing to take bold moves, be courageous.

   
   

3. What strategies have you employed to overcome gender-related obstacles in your AI career?

   
   

Never take NO for an answer because every seemingly "well meaning" advice I have encountered involved challenging the status quo. As minority in tech, from early age in school - being good at math, pursuing engineering, coming to US for grad school, going to IVY league for MBA involved continuously questioning and understanding the intrinsic thesis behind societal objections.

Being courageous, impatient, persistent and consistent has helped me to always look beyond, and ask WHY.

4. What advice would you give to young women aspiring to enter the field of AI?

   First and foremost - develop a growth and learning mindset because this is a very fast changing technology landscape. Do not get intimidated by a few boys /men or people who claim to know more.

   
   

   Follow the real innovators who are doing actual work, follow thought leaders, builders. Go to frequent meetups to learn -- from the ACM chapters, IEEE chapters to local meetups organized by folks. Silicon Valley of course has the most of these, but other areas too emerging. Also, do some side projects, leveraging the new AI tools - from nifty apps to some analysis. Also, I highly recommend building a good foundational knowledge in linear algebra, probability and statistics.

   
   

5. How do you think AI can be leveraged to celebrate and preserve women's history?

   I am not quite sure how to answer this. Given that most GenAI is trained on historical context and text documented only over the last couple of 100 years, available primarily in "English" -- there is quite a bit of work to be done to create data and investigate history to bring it to the digital realm. Similar to the effort on wikipedia -- this will require a lot of effort from public and private partnerships.

   
   

   Google for example is working closely with Indian universities to create Indic language datasets. As we create these, we also need to digitize content from all different languages, historical texts, literature in other languages.
   

Want to be the next in AI Spotlight? It’s a great opportunity to share your voice with our community!

🎊 Fill out the WxAI AI Spotlight Nomination Form for your chance to step into the AI Spotlight and to share your voice with the Women X AI community.